Biography
I am a final-year Ph.D. candidate at Cornell University, advised by Prof. Christina Delimitrou. I am broadly interested in improving the performance and efficiency of cloud systems. My recent research focuses on HW/SW co-design for ML systems. I was a research intern at Google Brain in 2021 and at Meta in 2022, 2024.
Before joining Cornell, I obtained my B.S. degree at Shanghai Jiao Tong University, advised by Prof. Chao Li.
I am actively looking for full-time job opportunities in industry.
Education
Ph.D. in Electrical and Computer Engineering, Cornell University, 2024 (expected)
Bachelor in Computer Science, Shanghai Jiao Tong University, 2019
Experience
Research intern: May 2024 - present
Meta, mentored by Krishna Malladi
Project: HW architecture design for ML inference
Research intern: May 2022 - Jan 2023
Meta, mentored by Wenyin Fu
Project: Production AI benchmarks generation
Research intern: May-Aug, 2021
Google Brain, mentored by Martin Maas
Project: Large-scale distributed ML workloads training and scheduling
Publications
Mingyu Liang, Hiwot Tadese Kassa, Wenyin Fu, Brian Coutinho, Louis Feng, and Christina Delimitrou. “Fine-grained Trace-driven Performance Modeling and Simulation for Large-scale ML Training”. In the Workshop on Machine Learning for Computer Architecture and Systems (MLArchSys), Buenos Aires, Argentina, June 2024. [pdf]
Mingyu Liang, Wenyin Fu, Louis Feng, Zhongyi Lin, Pavani Panakanti, Shengbao Zheng, Srinivas Sridharan, and Christina Delimitrou. “Mystique: Enabling Accurate and Scalable Generation of Production AI Benchmarks”. In 50th International Symposium on Computer Architecture (ISCA), Orlando, Florida, June 2023. [pdf]
Mingyu Liang*, Yu Gan*, Yueying Li, Carlos Torres, Abhishek Dhanotia, Mahesh Ketkar, and Christina Delimitrou. “Ditto: End-to-End Application Cloning for Networked Cloud Services”. In 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS), April 2023. Selected in IEEE Micro's Top Picks special issue of “most significant papers in computer architecture based on novelty and long-term impact” for 2023. [pdf]
Yu Gan, Mingyu Liang, Sundar Dev, David Lo, and Christina Delimitrou. “Sage: Practical & Scalable ML-Driven Performance Debugging in Microservices”. 26th ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS), April 2021. Selected in IEEE Micro's Top Picks special issue of “most significant papers in computer architecture based on novelty and long-term impact” for 2021. [pdf]
Zeyi Wen, Mingyu Liang, Bingsheng He and Zexin Xia. “High-Performance Index for Real-Time Matrix Retrieval”. IEEE Transactions on Knowledge and Data Engineering (TKDE), 2020. [pdf]
Xiaofeng Hou, Mingyu Liang, Chao Li, Wenli Zheng, Quan Chen, and Minyi Guo. “When Power Oversubscription Meets Traffic Flood Attack: Re-thinking Data Center Peak Load Management”. Proc. the 48th International Conference on Parallel Processing (ICPP), Aug. 2019. [pdf]
Honors & Awards
ML and Systems Rising Stars, ML Commons, 2023
IEEE Micro’s Top Picks, for the paper “Ditto: End-to-End Application Cloning for Networked Cloud Services”, 2023
IEEE Micro’s Top Picks, for the paper “Sage: Practical & Scalable ML-Driven Performance Debugging in Microservices”, 2021
Cornell Graduate Fellowship, 2019
Zhiyuan College Honors Scholarship, 2016, 2017
Teaching Experience
Computer Architecture (ECE 4750), Spring 2023
Embedding Systems (ECE 3140), Spring 2023
Datacenter Computing (ECE 5710), Spring 2021
Contact
Email: ml2585@cornell.edu
Address: Rhodes Hall 471C, Cornell University, Ithaca, NY, 14850